Graduate School of health and Medical Sciences

R for Data Science
Provider: Faculty of Health and Medical Sciences

Activity no.: 3335-25-00-00	There are 26 available seats
	Enrollment deadline: 02/06/2025

Date and time	16.06.2025, at: 08:30 - 18.06.2025, at: 16:00
Regular seats	35
Course fee	3,480.00 kr.
Lecturers	Anders Krogh
ECTS credits	2.30

Contact person	HeaDS Administration E-mail address: heads-admin@sund.ku.dk

Enrolment Handling/Course Organiser	PhD administration SUND E-mail address: phdkursus@sund.ku.dk

Aim and content This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrolment deadline, available seats will be allocated to the waiting list. The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at NorDoc member faculties. All other participants must pay the course fee. Learning objectives A student who has met the objectives of the course will be able to: • Explain and use the fundamental structure around R programming: R, R script, Quarto document, R project, R studio. • Perform advanced data wrangling/data management tasks using the tidyverse packages to organize and prepare data for analysis. • Perform exploratory data analysis with the ggplot2 package to spot patterns and trends in your data. • Perform and visualize principal component analysis (PCA) with the ggfortify packages to reveal the structure of the data. • Write and use R scripts by applying loops, conditionals, and functions to automate tasks and make your analysis more efficient. • Build and interpret models in R to analyze data, including linear regression, logistic regression, and clustering techniques. • Complete a full project in R from start to finish, including preparing your data, exploring it, running PCA, modeling, and presenting your results, while ensuring your analysis is reproducible and well-documented. Content The course R for Data Science is a continuation of our introductory course From Excel to R and it is therefore targeted towards people who already have some experience with R. The course starts by reinforcing the core R programming structure, including RStudio, R scripts, R projects, and Quarto documents. The focus then shifts to advanced data wrangling using the tidyverse to prepare data for analysis and exploratory data analysis (EDA) with ggplot2 to visualize patterns. Participants will also learn to perform PCA with ggfortify, automate tasks with R scripting (loops, conditionals, functions), and build basic models such as linear regression, logistic regression, and clustering. The course concludes with a full project, guiding participants from data preparation and exploration to modeling, while ensuring the work is reproducible and well-documented. By the end of the course, students will have the skills to manipulate, analyze, and visualize data in R, perform common models, and document their work effectively. Participants Seats: 35 The course R for Data Science is a continuation of our introductory course From Excel to R and it is therefore targeted towards people who already have some experience with R. Relevance to graduate programmers The course is relevant to PhD students from the following graduate programs at the Graduate School of Health and Medical Sciences, UCPH: All graduate programs Language English Form Lectures, interactive presentations from within R, group work, and exercises. N.B: Before the course starts participants must have installed the newest versions of R & Rstudio, as well as a list of packages provided by instructors, this is done to alleviate any installation issues on the course days. Anyone with installation issues can join for a technical help session on the first day of the course between 08:30 – 09:00. Course director Anders Krogh, Professor, Head of Center for Health Data Science, Center for Health Data Science, anders.krogh@sund.ku.dk Teachers Diana Andrejeva PhD, Data Scientist Center for Health Data Science andrejeva@sund.ku.dk Thilde Terkelsen PhD, Data Scientist Center for Health Data Science thilde.terkelsen@sund.ku.dk Helene Wegener Research Assistant Center for Health Data Science helene.wegener@sund.ku.dk Dates 16+17+18 June 2025 - 08:30 - 16:00 Course location Henrik Dam Auditorium Faculty of Health and Medical Sciences, Panum, Blegdamsvej 3B, 2200 København Registration Please register before 16 May 2025. Expected frequency The course will run again in Fall 2025. Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrolment. Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

Click the search button to search Courses.

See which courses you can attend and when

Jan	Feb	Mar	Apr
May	Jun	Jul	Aug
Sep	Oct	Nov	Dec

New courses
Courses are published regularly. High demand courses are announced in spring and autumn.

Learn which courses are announced on fixed dates